# Video Self-Supervised Learning

VideoMAEv2-Huge is a self-supervised learning-based video feature extraction model, pre-trained for 1200 epochs on the UnlabeledHybrid-1M dataset.

VideoMAE is a video self-supervised pretraining model based on Masked Autoencoder (MAE), fine-tuned on the Something-Something-v2 dataset for video classification tasks.

VideoMAE is a self-supervised video pre-training model based on masked autoencoder, pre-trained for 2400 epochs on the Something-Something-v2 dataset.

VideoMAE is a self-supervised video pre-training model based on masked autoencoder, fine-tuned on the Kinetics-400 dataset for video classification tasks.